Senior Machine Learning Engineer - Scene Understanding
Develops advanced Vision-Language-Action models for robotaxi scene understanding, detecting hazards and enabling safe driving. Leads data strategies, post-training of large models, and deployment using PyTorch and production ML pipelines. Requires MS/PhD in CS and deep learning expertise.
About the job
Responsibilities
- Design and train Vision-Language-Action (VLA) solutions for robotaxis
- Lead end-to-end data strategy, including mining, auto-labeling, and dataset construction to power our ML flywheel
- Lead the full post-training stack for VLMs and VLAs, including Continual Pre-training (CPT) on domain-specific driving data, Supervised Fine-Tuning (SFT) for instruction following
- Utilize our large-scale data pipelines and ML infrastructure to research, prototype, and deploy solutions that improve driving behavior
- Partner with cross-functional teams to integrate perception signals
Qualifications
- MS or PhD in Computer Science or related field
- Background in deep learning solutions for VLM and VLA models
- Track record in post-training large-scale models, CPT, SFT, RL
- Hands-on experience with production ML pipelines, including dataset creation, training frameworks, and metrics
- Expertise in Python libraries (PyTorch, NumPy, Pandas, VLLM)
Bonus Qualifications
- Deep knowledge of cutting-edge computer vision techniques
- Publications in top-tier conferences (CVPR, ICCV, RSS, ICRA)
- Experience with integrating large language models to various tasks
Skills
PyTorch, NumPy, pandas, vLLM, Vision-Language-Action, Vla, Vision-Language Models, Vlm, Continual Pre-Training, Cpt, Supervised Fine-Tuning, Sft, Reinforcement Learning, Rl, Computer Vision
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